Dr Qiang Zhu

Group leader

Principal investigator

qiangzhu@uow.edu.au
Building 41, Room 116.F1

Dr Qiang Zhu is a computational chemist and biophysicist dedicated to advancing molecular simulations for solving challenging problems in chemistry, biology, and medicine. His research combines theoretical modelling, high-performance computing, and artificial intelligence to understand how molecules assemble, interact, and function in complex environments.

His current research focuses on biomolecular condensates, protein aggregation, drug discovery, and multiscale simulation method development. By creating new computational tools and integrating physics-based and AI-driven approaches, he seeks to reveal molecular mechanisms that are difficult to access experimentally and to accelerate the translation of fundamental discoveries into biomedical and technological applications.

Dr Zhu earned his PhD from Nanjing University and completed postdoctoral training at both Nanjing University and the University of California, Irvine. He is currently a Vice-Chancellor’s Research Fellow at the University of Wollongong, where he leads research on computational methods for biomolecular systems and therapeutic discovery.

Publications

Group list →

Deep-Penetrating Transdermal Lipopeptide Liposomes for Sustained IL-17 Inhibition and Prevention of Psoriatic Recurrence

R. Cong, S. Zhou, L. Li, F. Li, J. Ren, Q. Zhu, H. Yang, J. Tu, X. Jiang, L. Jiang

Journal of the American Chemical Society 148, 27884–27899 (2026) · DOI · mechanisms understanding

Firefly-Geni: Automated Iteration-Guided Generative Discovery of TADF Molecules

B. Zhang, X. Fang, D. Yang, Y. Wang, Y. Liu, Y. Xia, Q. Zhu, H. Yu, M. Zhu, J. Wen

(2026) · DOI · machine learning

Mechanistic Insights into Nanobody-Based Quenchbody Sensing via Structural Modeling and Molecular Simulations

N. S. El Salamouni, J. H. Cater, Q. Zhu, L. M. Spenkelink, H. Yu

Journal of Chemical Information and Modeling 66, 2879–2888 (2026) · DOI · mechanisms understanding

N-Terminal Chirality and Sequence Variations Modulate the Conformational Landscape of Amyloid-Beta 42

Q. Zhu, H. Yu

Journal of Chemical Information and Modeling 66, 10156–10167 (2026) · DOI · Code · mechanisms understanding

Relay Storage of Protons and Zinc Ions Enables Practical High‐Mass‐Loading Organic Electrodes

X. Yu, S. Yuan, L. Yan, T. Kong, K. Zhou, Y. Qi, Q. Zhu, Z. Li, P. Wang, S. Gu, J. Ma, Y. Wang

Angewandte Chemie 138 (2026) · DOI · mechanisms understanding

Automated Refinement of Property-Specific Polarizable Gaussian Multipole Water Models Using Bayesian Black-Box Optimization

Y. Wu, Q. Zhu, Z. Huang, P. Cieplak, Y. Duan, R. Luo

Journal of Chemical Theory and Computation 21, 3563–3575 (2025) · DOI · machine learning

Biomolecular Condensates as Emerging Biomaterials: Functional Mechanisms and Advances in Computational and Experimental Approaches

Q. Zhu, Z. Raza, D. Do‐Ha, E. De Costa, P. Sasheva, L. McAlary, H. Mahmodi, W. P. Bowen, L. Ooi, I. Kabakova, H. Yu

Advanced Materials 37 (2025) · DOI · biomolecular condensatescoarse-grained

Bridging Dimensionality Reduction and Stochastic Sampling: The DA2-MC Algorithm for Protein Dynamics

R. Shen, Q. Zhu, L. Hu, J. Ma, W. Wang, H. Dong

The Journal of Physical Chemistry Letters 16, 4788–4795 (2025) · DOI · machine learningenhanced sampling

Coarse-grained models for ionic liquids and applications to biological and electrochemical systems

Y. Ge, Q. Zhu, X. Wang, J. Ma

Industrial Chemistry & Materials 3, 383–411 (2025) · DOI · machine learningcoarse-grained

Decoding Hairpin Structure Stability in Lin28-Mediated Repression

Q. Zhu, L. Hu, C. Cui, M. Zang, H. Dong, J. Ma

Biochemistry 64, 1276–1284 (2025) · DOI · mechanisms understanding

End-to-End Modeling of Reaction Field Energy Using Data-Driven Geometric Graph Neural Networks

Y. Wu, Q. Zhu, R. Luo

Journal of Chemical Theory and Computation 21, 9710–9725 (2025) · DOI · machine learningproperties prediction

External electric field control of charge transport in Y-shaped and linear non-fullerene acceptors

L. Fu, J. Hu, R. Li, H. Geng, Q. Zhu, Z. Fan, B. Cheng

Journal of Materials Chemistry A 13, 37854–37863 (2025) · DOI · mechanisms understanding

LightChem: A Lightweight Domain-Specific Language Model for Molecular Property and Reaction Prediction in Chemistry

Yu Zhang, J. Zhang, Y. Gu, Q. Tao, L. He, D. Li, Yijian Zhang, Dingwen Fan, Yijie Gao, J. Sun, J. Chen, R. Shi, Z. Wu, Q. Jia, L. Zheng, S. Yuan, F. Yang, Y. Chen, D. Zheng, Yilin Liu, Y. Cai, Z. Gu, C. Zhang, B. Cai, G. Li, Tianyu Zhang, Y. Zhou, Yuang Liu, Tianyue Zhang, S. Xing, Z. Li, X. Su, Dong Fan, H. Qian, X. Li, B. Zhang, Y. Xiao, X. Liu, Y. Zhu, Q. Zhu, Q. Liu, S. Chen, J. Wen, Z. Yu, G. Zeng, Y. Liang, Y. Wang, W. Xu, J. Wang, M. Yang, Yang Gao, S. Li, Y. Shi, X. Chen, H. Dong, W. Li, J. Ma, G. Wang

(2025) · DOI · machine learningproperties prediction

Proton coordination chemistry in pyrene-based anodes for ultralong-life aqueous proton batteries

W. Yang, C. Zhan, Q. Zhu, L. Liu, B. Su, H. Yu, L. Zhang, L. Yan, J. Shu

Inorganic Chemistry Frontiers 12, 4213–4222 (2025) · DOI · mechanisms understanding

Prediction of free radical reactions toward organic pollutants with easily accessible molecular descriptors

G. Zhang, Q. Zhu, H. Zheng, S. Zhang, J. Ma

Chemosphere 346, 140660 (2024) · DOI · machine learningproperties prediction

Shifting redox reaction equilibria on demand using an orthogonal redox cofactor

D. Aspacio, Y. Zhang, Y. Cui, E. Luu, E. King, W. B. Black, S. Perea, Q. Zhu, Y. Wu, R. Luo, J. B. Siegel, H. Li

Nature Chemical Biology 20, 1535–1546 (2024) · DOI · mechanisms understanding

Single-molecule sensing inside stereo- and regio-defined hetero-nanopores

W. Liu, Q. Zhu, C.-N. Yang, Y.-H. Fu, J.-C. Zhang, M.-Y. Li, Z.-L. Yang, K.-L. Xin, J. Ma, M. Winterhalter, Y.-L. Ying, Y.-T. Long

Nature Nanotechnology 19, 1693–1701 (2024) · DOI · mechanisms understanding

Targeting SHP2 Cryptic Allosteric Sites for Effective Cancer Therapy

A. U. Rehman, C. Zhao, Y. Wu, Q. Zhu, R. Luo

International Journal of Molecular Sciences 25, 6201 (2024) · DOI · mechanisms understanding

Understanding and fine tuning the propensity of ATP-driven liquid–liquid phase separation with oligolysine

Q. Zhu, Y. Wu, R. Luo

Physical Chemistry Chemical Physics 26, 10568–10578 (2024) · DOI · biomolecular condensatescoarse-grained

AmberTools

D. A. Case, H. M. Aktulga, K. Belfon, D. S. Cerutti, G. A. Cisneros, V. W. D. Cruzeiro, N. Forouzesh, T. J. Giese, A. W. Götz, H. Gohlke, S. Izadi, K. Kasavajhala, M. C. Kaymak, E. King, T. Kurtzman, T.-S. Lee, P. Li, J. Liu, T. Luchko, R. Luo, M. Manathunga, M. R. Machado, H. M. Nguyen, K. A. O’Hearn, A. V. Onufriev, F. Pan, S. Pantano, R. Qi, A. Rahnamoun, A. Risheh, S. Schott-Verdugo, A. Shajan, J. Swails, J. Wang, H. Wei, X. Wu, Y. Wu, S. Zhang, S. Zhao, Q. Zhu, T. E. Cheatham, D. R. Roe, A. Roitberg, C. Simmerling, D. M. York, M. C. Nagan, K. M. Merz

Journal of Chemical Information and Modeling 63, 6183–6191 (2023) · DOI · method development

Grid-Robust Efficient Neural Interface Model for Universal Molecule Surface Construction from Point Clouds

Y. Wu, H. Wei, Q. Zhu, R. Luo

The Journal of Physical Chemistry Letters 14, 9034–9041 (2023) · DOI · method developmentmachine learning

Machine Learning-Guided Adaptive Parametrization for Coupling Terms in a Mixed United-Atom/Coarse-Grained Model for Diphenylalanine Self-Assembly in Aqueous Ionic Liquids

Y. Ge, X. Wang, Q. Zhu, Y. Yang, H. Dong, J. Ma

Journal of Chemical Theory and Computation 19, 6718–6732 (2023) · DOI · method developmentmachine learningcoarse-grained

Planar Chirality for Acid/Base Responsive Macrocyclic Pillararenes Induced by Amino Acid Derivatives: Molecular Dynamics Simulations and Machine Learning

L. Fu, R. Wang, Q. Zhu, Y. Gu, L. Zheng, Y. Chen, J. Jiang, J. Ma

Journal of Chemical Theory and Computation 19, 4364–4376 (2023) · DOI · machine learning

Recent Advances in Biomolecular Recognition

Q. Zhu, R. Luo

International Journal of Molecular Sciences 24, 8310 (2023) · DOI

Streamlining and Optimizing Strategies of Electrostatic Parameterization

Q. Zhu, Y. Wu, S. Zhao, P. Cieplak, Y. Duan, R. Luo

Journal of Chemical Theory and Computation 19, 6353–6365 (2023) · DOI · Code · method developmentpolarisable force field

Treating Polarization Effects in Charged and Polar Bio-Molecules Through Variable Electrostatic Parameters

Q. Zhu, Y. Ge, W. Li, J. Ma

Journal of Chemical Theory and Computation 19, 396–411 (2023) · DOI · polarisable force field

An electrostatic-variable coarse-grained model for predicting enthalpy of vaporization, surface tension, diffusivity, conductivity, and dielectric constant of aqueous ionic liquid

Y. Ge, Q. Zhu, Y. Li, H. Dong, J. Ma

Journal of Molecular Liquids 346, 118230 (2022) · DOI · method developmentcoarse-grained

Batch-Scale Synthesis of Nanoparticle-Agminated Three-Dimensional Porous Cu@Cu2O Microspheres for Highly Selective Electrocatalysis of Nitrate to Ammonia

M. Jiang, Q. Zhu, X. Song, Y. Gu, P. Zhang, C. Li, J. Cui, J. Ma, Z. Tie, Z. Jin

Environmental Science & Technology 56, 10299–10307 (2022) · DOI · mechanism understanding

Fast Prediction of Lipophilicity of Organofluorine Molecules: Deep Learning-Derived Polarity Characters and Experimental Tests

Q. Jia, Y. Ni, Z. Liu, X. Gu, Z. Cui, M. Fan, Q. Zhu, Y. Wang, J. Ma

Journal of Chemical Information and Modeling 62, 4928–4936 (2022) · DOI · method developmentmachine learningproperties prediction

Identification of Single-Molecule Catecholamine Enantiomers Using a Programmable Nanopore

W. Jia, C. Hu, Y. Wang, Y. Liu, L. Wang, S. Zhang, Q. Zhu, Y. Gu, P. Zhang, J. Ma, H.-Y. Chen, S. Huang

ACS Nano 16, 6615–6624 (2022) · DOI · mechanism understanding

Machine learning assisted prediction of charge transfer properties in organic solar cells by using morphology-related descriptors

L. Fu, H. Hu, Q. Zhu, L. Zheng, Y. Gu, Y. Wen, H. Ma, H. Yin, J. Ma

Nano Research 16, 3588–3596 (2022) · DOI · machine learning

Molecular partition coefficient from machine learning with polarization and entropy embedded atom-centered symmetry functions

Q. Zhu, Q. Jia, Z. Liu, Y. Ge, X. Gu, Z. Cui, M. Fan, J. Ma

Physical Chemistry Chemical Physics 24, 23082–23088 (2022) · DOI · method developmentmachine learningproperties prediction

Surface Stability and Morphology of Calcium Phosphate Tuned by pH Values and Lactic Acid Additives: Theoretical and Experimental Study

Hongwei Chen, C. Lv, L. Guo, M. Ma, X. Li, Z. Lan, J. Huo, H. Dong, X. Zhu, Q. Zhu, Y. Gu, Z. Liu, J. Liu, Hangrong Chen, X. Guo, J. Ma

ACS Applied Materials & Interfaces 14, 4836–4851 (2022) · DOI · mechanism understanding

Towards High‐Performance Aqueous Zinc Batteries via a Semi‐Conductive Bipolar‐Type Polymer Cathode

L. Yan, Q. Zhu, Y. Qi, J. Xu, Y. Peng, J. Shu, J. Ma, Y. Wang

Angewandte Chemie International Edition 61 (2022) · DOI · mechanism understanding

Shear viscosity prediction of alcohols, hydrocarbons, halogenated, carbonyl, nitrogen-containing, and sulfur compounds using the variable force fields

Q. Zhu, Y. Gu, L. Hu, T. Gaudin, M. Fan, J. Ma

The Journal of Chemical Physics 154 (2021) · DOI · machine learning

A Two-Ended Data-Driven Accelerated Sampling Method for Exploring the Transition Pathways between Two Known States of Protein

Y. Yuan, Q. Zhu, R. Song, J. Ma, H. Dong

Journal of Chemical Theory and Computation 16, 4631–4640 (2020) · DOI · method developmentmachine learning

A Data‐Driven Accelerated Sampling Method for Searching Functional States of Proteins

Q. Zhu, Y. Yuan, J. Ma, H. Dong

Advanced Theory and Simulations 2 (2019) · DOI · method developmentmachine learning

Direct Extracellular Electron Transfer of the Geobacter sulfurreducens Pili Relevant to Interaromatic Distances

C. Shu, Q. Zhu, K. Xiao, Y. Hou, H. Ma, J. Ma, X. Sun

BioMed Research International 2019, 1–12 (2019) · DOI · mechanism understanding

On-Demand Electrical Switching of Antibody?Antigen Binding on Surfaces

B. Santos Gomes, E. Cantini, S. Tommasone, J. S. Gibson, X. Wang, Q. Zhu, J. Ma, J. D. McGettrick, T. M. Watson, J. A. Preece, J. C. Kirkman-Brown, S. J. Publicover, P. M. Mendes

ACS Applied Bio Materials 1, 738–747 (2018) · DOI · mechanism understanding

Synergistic steric pairing effects of terfluorenes with ternary side groups on β-conformation transition: experiments and computations

X.-A. Yuan, M.-N. Yu, Q. Zhu, W.-W. Zhang, L.-H. Xie, W. Huang, J. Ma

Journal of Materials Chemistry C 6, 1551–1561 (2018) · DOI · mechanism understanding

Electrostatic Interactions of Water in External Electric Field: Molecular Dynamics Simulations

Q. Zhu, Z. KAN, J. Ma

Journal of Electrochemistry 23, 4 (2017) polarisation effects

Entropy and Polarity Control the Partition and Transportation of Drug-like Molecules in Biological Membrane

Q. Zhu, Y. Lu, X. He, T. Liu, H. Chen, F. Wang, D. Zheng, H. Dong, J. Ma

Scientific Reports 7 (2017) · DOI · mechanism understandingpolarisation effects

Polarization Effects on the Cellulose Dissolution in Ionic Liquids: Molecular Dynamics Simulations with Polarization Model and Integrated Tempering Enhanced Sampling Method

Z. Kan, Q. Zhu, L. Yang, Z. Huang, B. Jin, J. Ma

The Journal of Physical Chemistry B 121, 4319–4332 (2017) · DOI · mechanism understandingpolarisation effects

Tuning the collective switching behavior of azobenzene/Au hybrid materials: flexible versus rigid azobenzene backbones and Au(111) surfaces versus curved Au nanoparticles

C. Liu, D. Zheng, W. Hu, Q. Zhu, Z. Tian, J. Zhao, Y. Zhu, J. Ma

Nanoscale 9, 16700–16710 (2017) · DOI · mechanism understanding

← Back to the team